> Markdown version of [/jobs/ext/1897035-datacenter-gpu-power-architect](https://www.wearedevelopers.com/jobs/ext/1897035-datacenter-gpu-power-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Datacenter GPU Power Architect - **Company:** NVIDIA Ltd. - **Location:** United States - **Salary:** $100,000.0 - $166,750.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Computer Engineering, Data Centers, Microprocessors, Python (Programming Language), Machine Learning, NumPy, Software Architecture, Systems Architecture, Scripting, Graphics Processing Unit (GPU), Computer Network Operations, High Performance Computing, Pytorch, Pandas, Perf (Linux), Power Analysis (Cryptography) - **Published:** July 31, 2026 - **Apply:** https://www.careerbuilder.com/job-details/gpu-power-architect-new-college-grad-2026-ca--a903b75f-9023-4dbe-ad43-2fc25b4bdce7 ## About the Role * Pursuing or recently completed a Bachelors or Masters in Electrical Engineering, Computer Engineering, or equivalent experience * Knowledge of energy efficient chip design fundamentals and related tradeoffs. * Familiarity with low power design techniques such as multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS). * Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques. * Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch. * Familiarity with performance monitors/simulators used in modern processor architectures., Artificial Intelligence (AI), CPU (Central Processing Unit), Computer Engineering, Data Analysis, Develop Methodologies, Electrical Engineering, Energy Efficiency, GPU (Graphics Processing Unit), Low Power, Machine Learning, Microprocessor Architecture, Mobile Devices, Network Operations Center, Performance Analysis, Performance Modeling, Python Programming/Scripting Language, Research & Development (R&D), Software Architecture, System Architecture, Total Cost of Ownership ## Description NVIDIA is known as a world leader in providing energy-efficient high-performance products and we continue to invest in the research and development of hyper-efficient GPU and SOC architectures. We are continually innovating in creative and unrivaled ways to improve our ability to deliver exceptional Perf/Watt solutions in a wide range of sectors and verticals. Come join NVIDIAs Applied Power Architecture team to develop state of the art GPUs to power AI, HPC, Automotive, GeForce, and Mobile products. What you'll be doing: * You will be contributing to power estimation models and tools for GPU products and systems like NVIDIA DGX. * Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level. * You will help with Performance vs Power Analysis for NVIDIA future product lineup. * Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs, CPUs, Switches, and platforms. * Understand the workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements. * Modeling & analysis of cutting-edge technologies like high speed & high-density interconnects. ## Related Videos - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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